YAO LU^1,2,*, QIUYUE WANG¹, CAIHUI ZHANG¹

BIOCELL, Vol.47, No.2, pp. 393-400, 2023, DOI:10.32604/biocell.2023.024944

Abstract Myocardial fibrosis is an important manifestation of diabetic cardiomyopathy. This study investigated the potential mechanism of diabetic myocardial fibrosis. Male C57BL/6J and db/db mice aged 8 weeks were randomly divided into the diabetic (DB) and control groups. At 20 weeks, the mouse heart was harvested and subjected to hematoxylin-eosin staining (HE) and Masson staining to investigate the degree of fibrosis. The expressions of transforming growth factor-beta 1 (TGF-β1), collagen-III, B-cell lymphoma-2 (Bcl2), Bcl2-associated X protein (Bax), cleaved gasdermin D (GSDMD), cysteinyl aspartate specific proteinase-1 (caspase-1), apoptosis-associated speck-like protein containing a CARD (ASC), and nucleotide-binding oligomerization domain (NOD)-like receptor 3 (NLRP3)… More >

S. Sudha^*, A. Srinivasan, T. Gayathri Devi

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1985-2000, 2023, DOI:10.32604/csse.2023.030960

Abstract The substantial vision loss due to Diabetic Retinopathy (DR) mainly damages the blood vessels of the retina. These feature changes in the blood vessels fail to exist any manifestation in the eye at its initial stage, if this problem doesn’t exhibit initially, that leads to permanent blindness. So, this type of disorder can be only screened and identified through the processing of fundus images. The different stages in DR are Micro aneurysms (Ma), Hemorrhages (HE), and Exudates, and the stages in lesion show the chance of DR. For the advancement of early detection of DR in the eye we have… More >

N. M. Balamurugan^1,*, K. Maithili², T. K. S. Rathish Babu³, M. Adimoolam⁴

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 499-514, 2023, DOI:10.32604/iasc.2023.031661

Abstract Diabetic Eye Disease (DED) is a fundamental cause of blindness in human beings in the medical world. Different techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy (DR). The Machine Learning (ML) and the Deep Learning (DL) algorithms are the predominant techniques to project and explore the images of DR. Even though some solutions were adapted to challenge the cause of DR disease, still there should be an efficient and accurate DR prediction to be adapted to refine its performance. In this work, a hybrid technique was proposed for classification and prediction of DR. The… More >

R. Nandakumar¹, P. Saranya^2,*, Vijayakumar Ponnusamy³, Subhashree Hazra², Antara Gupta²

Computer Systems Science and Engineering, Vol.45, No.1, pp. 279-292, 2023, DOI:10.32604/csse.2023.028703

Abstract A prevalent diabetic complication is Diabetic Retinopathy (DR), which can damage the retina’s veins, leading to a severe loss of vision. If treated in the early stage, it can help to prevent vision loss. But since its diagnosis takes time and there is a shortage of ophthalmologists, patients suffer vision loss even before diagnosis. Hence, early detection of DR is the necessity of the time. The primary purpose of the work is to apply the data fusion/feature fusion technique, which combines more than one relevant feature to predict diabetic retinopathy at an early stage with greater accuracy. Mechanized procedures for… More >

V. Thanikachalam^1,*, M. G. Kavitha², V. Sivamurugan¹

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2129-2145, 2023, DOI:10.32604/csse.2023.026527

Abstract In recent times, Internet of Things (IoT) and Deep Learning (DL) models have revolutionized the diagnostic procedures of Diabetic Retinopathy (DR) in its early stages that can save the patient from vision loss. At the same time, the recent advancements made in Machine Learning (ML) and DL models help in developing Computer Aided Diagnosis (CAD) models for DR recognition and grading. In this background, the current research works designs and develops an IoT-enabled Effective Neutrosophic based Segmentation with Optimal Deep Belief Network (ODBN) model i.e., NS-ODBN model for diagnosis of DR. The presented model involves Interval Neutrosophic Set (INS) technique… More >

A. Deepak Kumar^1,2,*, T. Sasipraba¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2273-2288, 2023, DOI:10.32604/iasc.2023.028996

Abstract Diabetic Retinopathy is a disease, which happens due to abnormal growth of blood vessels that causes spots on the vision and vision loss. Various techniques are applied to identify the disease in the early stage with different methods and parameters. Machine Learning (ML) techniques are used for analyzing the images and finding out the location of the disease. The restriction of the ML is a dataset size, which is used for model evaluation. This problem has been overcome by using an augmentation method by generating larger datasets with multidimensional features. Existing models are using only one augmentation technique, which produces… More >

Monika Saraswat^*, A. K. Wadhwani, Sulochana Wadhwani

Journal on Artificial Intelligence, Vol.4, No.2, pp. 61-76, 2022, DOI:10.32604/jai.2022.028140

Abstract Today, more families are affected by Diabetes Mellitus (DM) disease on account of its continually increasing occurrence. Most patients remain unknown about their health quality or the DM’s risk factors prior to diagnosis. The medical world has witnessed that individuals are affected by two different diabetes namely a) Type-1 diabetes (T1D), as well as b) Type-2 diabetes (T2D). As Type 2 Diabetes affects the other organs of the body, the proposed system concentrates specifically on Type 2 Diabetes. This work aims to ascertain the cardiac disorder in T2D patients. As of the ECG dataset, the requisite data is gathered it… More >

Ghassan Ahmed Ali¹, Thamer Mitib Ahmad Al Sariera^2,*, Muhammad Akram¹, Adel Sulaiman¹, Fekry Olayah¹

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1601-1616, 2023, DOI:10.32604/csse.2023.026119

Abstract Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the image is divided into sub-images… More >

M. P. Karthikeyan^1,*, E. A. Mary Anita²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 567-580, 2023, DOI:10.32604/iasc.2023.026243

Abstract In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indicator of diabetic retinopathy. With that in mind, the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine… More >

Kuntal Das¹, Syed Mohammed Basheeruddin Asdaq^2,*, M. Saifulla Khan^1,*, Sravani Singirikonda¹, Abdulhakeem S. Alamri^3,4, Walaa F. Alsanie^3,4, Majid Alhomrani^3,4, Sreeharsha Nagaraja^5,6, Katharigatta N. Venugopala^5,7

Phyton-International Journal of Experimental Botany, Vol.91, No.10, pp. 2349-2365, 2022, DOI:10.32604/phyton.2022.022379

Abstract The current study used RP-HPLC to compare phytochemicals and estimate the bioactive constituents found in Stevia rebaudiana Bert. (SRB) leaves collected from two different geographical sources. SRB leaves were collected from Bangalore, Karnataka, India, and Reduit, Mauritius. Extracts were prepared using ethanol and aqueous solvents. Proximate analysis was used to evaluate moisture content, ash values, crude fibers, and extractive values. Following that, preliminary phytochemical screening was done on both ethanol leaves extracts, and subsequently total flavonoid content was determined. In addition, TLC chromatograms and RP-HPLC studies were performed on both plant extracts to determine the presence of flavonoid components in… More >